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Recent studies have shown that in the presence of noise both fronts propagating into a metastable state and so-called pushed fronts propagating into an unstable state, exhibit diffusive wandering about the average position. In this paper we…

Statistical Mechanics · Physics 2016-08-31 Andrea Rocco , Jaume Casademunt , Ute Ebert , Wim van Saarloos

We establish the $L^2$-solvability of Dirichlet, Neumann and regularity problems for divergence-form heat (or diffusion) equations with H\"older-continuous diffusion coefficients, on bounded Lipschitz domains in $\mathbb{R}^n$. This is…

Analysis of PDEs · Mathematics 2023-10-25 Alejandro J. Castro , Salvador Rodríguez-López , Wolfgang Staubach

Score-based generative modeling, implemented through probability flow ODEs, has shown impressive results in numerous practical settings. However, most convergence guarantees rely on restrictive regularity assumptions on the target…

Machine Learning · Statistics 2025-10-21 Gitte Kremling , Francesco Iafrate , Mahsa Taheri , Johannes Lederer

We study the asymptotic error of score-based diffusion model sampling in large-sample scenarios from a non-parametric statistics perspective. We show that a kernel-based score estimator achieves an optimal mean square error of…

Statistics Theory · Mathematics 2024-07-25 Kaihong Zhang , Caitlyn H. Yin , Feng Liang , Jingbo Liu

The behavior of slow-fast diffusions as the separation of scale diverges is a well-studied problem in the literature. In this short paper, we revisit this problem and obtain a new proof of existing strong quantitative convergence estimates…

Optimization and Control · Mathematics 2025-10-28 Sumith Reddy Anugu , Vivek S. Borkar

For nonexpansive fixed-point problems, Halpern's method with optimal parameters, its so-called H-dual algorithm, and in fact, an infinite family of algorithms containing them, all exhibit the exactly minimax optimal convergence rates. In…

Optimization and Control · Mathematics 2025-11-20 TaeHo Yoon , Ernest K. Ryu , Benjamin Grimmer

The nonparametric estimation of the volatility and the drift coefficient of a scalar diffusion is studied when the process is observed at random time points. The constructed estimator generalizes the spectral method by Gobet, Hoffmann and…

Statistics Theory · Mathematics 2017-10-12 Jakub Chorowski , Mathias Trabs

How can we interpret the infimum of Lipschitz constants in a conjugacy class of interval maps? For positive entropy maps, the exponential of the topological entropy gives a well-known lower bound. We show that for piecewise monotone…

Dynamical Systems · Mathematics 2021-04-07 Jozef Bobok , Samuel Roth

We are interested in the inverse problem of recovering a Robin coefficient defined on some non accessible part of the boundary from available data on another part of the boundary in the nonstationary Stokes system. We prove a Lipschitz…

Analysis of PDEs · Mathematics 2013-09-11 Anne-Claire Egloffe

In this paper, we propose a drift-diffusion process on the probability simplex to study stochastic fluctuations in probability spaces. We construct a counting process for linear detailed balanced chemical reactions with finite species such…

Probability · Mathematics 2024-08-19 Yuan Gao , Wuchen Li , Jian-Guo Liu

We provide an asymptotic analysis of linear transport problems in the diffusion limit under minimal regularity assumptions on the domain, the coefficients, and the data. The weak form of the limit equation is derived and the convergence of…

Analysis of PDEs · Mathematics 2014-07-31 Herbert Egger , Matthias Schlottbom

We consider the reconstruction of a diffusion coefficient in a quasilinear elliptic problem from a single measurement of overspecified Neumann and Dirichlet data. The uniqueness for this parameter identification problem has been established…

Numerical Analysis · Mathematics 2015-06-17 Herbert Egger , Jan-Frederik Pietschmann , Matthias Schlottbom

We consider a particle moving with equation of motion $\dot x=f(t)$, where $f(t)$ is a random function with statistics which are independent of $x$ and $t$, with a finite drift velocity $v=\langle f\rangle$ and in the presence of a…

Chaotic Dynamics · Physics 2016-08-24 Robin Guichardaz , Alain Pumir , Michael Wilkinson

We discuss the effective diffusion constant $D_{{\it eff}}$ for stochastic processes with spatially-dependent noise. Starting from a stochastic process given by a Langevin equation, different drift-diffusion equations can be derived…

Statistical Mechanics · Physics 2026-02-16 Stefano Giordano , Ralf Blossey

Flow Matching, a promising approach in generative modeling, has recently gained popularity. Relying on ordinary differential equations, it offers a simple and flexible alternative to diffusion models, which are currently the…

Machine Learning · Statistics 2026-03-13 Lea Kunkel

We revisit the variational characterization of diffusion as entropic gradient flux and provide for it a probabilistic interpretation based on stochastic calculus. It was shown by Jordan, Kinderlehrer, and Otto that, for diffusions of…

Probability · Mathematics 2020-03-24 Ioannis Karatzas , Walter Schachermayer , Bertram Tschiderer

In Lipschitz domains, we study a Darcy-Forchheimer problem coupled with a singular heat equation by a nonlinear forcing term depending on the temperature. By singular we mean that the heat source corresponds to a Dirac measure. We establish…

Numerical Analysis · Mathematics 2023-04-25 Alejandro Allendes , Gilberto Campaña , Enrique Otarola

This paper deals with an inverse source problem for the $1$D time-fractional diffusion equation by using boundary measurement. The conditional stability in identification of the unknown source term is proved on the basis of the Fourier…

Analysis of PDEs · Mathematics 2016-08-25 Zhiyuan Li

We consider nonparametric Bayesian inference in a reflected diffusion model $dX_t = b (X_t)dt + \sigma(X_t) dW_t,$ with discretely sampled observations $X_0, X_\Delta, \dots, X_{n\Delta}$. We analyse the nonlinear inverse problem…

Statistics Theory · Mathematics 2020-05-26 Richard Nickl , Jakob Söhl

The recent, impressive advances in algorithmic generation of high-fidelity image, audio, and video are largely due to great successes in score-based diffusion models. A key implementing step is score matching, that is, the estimation of the…

Machine Learning · Statistics 2024-09-12 Zehao Dou , Subhodh Kotekal , Zhehao Xu , Harrison H. Zhou